移动边缘计算中基于Stackelberg博弈的算力交易与定价

针对移动边缘计算中轻量级智能设备计算和存储能力有限等问题，提出一种基于Stackelberg博弈的计算卸载解决方案。首先，结合区块链技术构建基于云挖掘机制的算力交易模型——CPTP-BSG，允许移动智能设备（矿工）将密集且复杂的计算任务卸载到边缘服务器；其次，将矿工与边缘计算服务提供商（ESP）之间的算力交易建模为一个两阶段的Stackelberg博弈过程，并构建矿工与ESP的预期利润函数；然后，使用逆向归纳法分别在统一定价和歧视性定价策略下分析纳什均衡解的存在性和唯一性；最后，提出一种低梯度迭代算法来实现矿工和ESP的利润最大化。实验结果证明了所提算法的有效性，并且与统一定价相比，歧视性定价更符合矿工的个性化算力需求，能达到更高的算力需求总量和ESP利润。

Computing power trading and pricing in mobile edge computing based on Stackelberg game

Concerning the problem of limited computing capacity and storage capacity of lightweight smart devices in mobile edge computing, a computational offloading solution based on Stackelberg game was proposed. First, Combining with the blockchain technology, a computing power trading model based on cloud mining mechanism, named CPTP-BSG (Computing Power Trading and Pricing with Blockchain and Stackelberg Game), was built, which allows mobile smart devices (miners) to offload intensive and complex computing tasks to edge servers. Second, the computing power trading between miners and Edge computing Service Providers (ESPs) was modeled as a two-stage Stackelberg game process, and the expected profit functions for miners and ESP were formulated. Then, the existence and uniqueness of Nash equilibrium solution were respectively analyzed under uniform pricing and discriminatory pricing strategies by backward induction. Finally, a low gradient iterative algorithm was proposed to maximize the profits of miners and ESP. Experimental results show the effectiveness of the proposed algorithm, and it can be seen that the discriminatory pricing is more in line with the personalized computing power demand of miners than uniform pricing, and can achieve higher total demand of computing power and ESP profit.